89 lines
2.8 KiB
Java
89 lines
2.8 KiB
Java
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package eu.dnetlib.dhp.oa.graph.dump.ttl;
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import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
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import java.io.Serializable;
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import java.util.ArrayList;
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import java.util.Optional;
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import java.util.Set;
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import java.util.stream.Collectors;
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import org.apache.commons.io.IOUtils;
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import org.apache.hadoop.io.compress.GzipCodec;
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import org.apache.spark.SparkConf;
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import org.apache.spark.api.java.function.MapFunction;
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import org.apache.spark.sql.Dataset;
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import org.apache.spark.sql.Encoders;
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import org.apache.spark.sql.SaveMode;
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import org.apache.spark.sql.SparkSession;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.oa.graph.dump.Utils;
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import eu.dnetlib.dhp.schema.oaf.Organization;
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import scala.Tuple2;
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public class SparkPrepareOrganizationInfo implements Serializable {
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private static final Logger log = LoggerFactory.getLogger(SparkPrepareOrganizationInfo.class);
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public static void main(String[] args) throws Exception {
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String jsonConfiguration = IOUtils
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.toString(
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SparkPrepareOrganizationInfo.class
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.getResourceAsStream(
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"/eu/dnetlib/dhp/oa/graph/dump_whole/input_organization_parameters.json"));
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final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
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parser.parseArgument(args);
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Boolean isSparkSessionManaged = Optional
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.ofNullable(parser.get("isSparkSessionManaged"))
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.map(Boolean::valueOf)
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.orElse(Boolean.TRUE);
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log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
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final String inputPath = parser.get("sourcePath");
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log.info("inputPath: {}", inputPath);
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final String outputPath = parser.get("outputPath");
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log.info("outputPath: {}", outputPath);
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SparkConf conf = new SparkConf();
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runWithSparkHiveSession(
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conf,
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isSparkSessionManaged,
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spark -> {
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Utils.removeOutputDir(spark, outputPath);
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prepareOrganization(spark, inputPath, outputPath);
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});
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}
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private static void prepareOrganization(SparkSession spark, String inputPath, String outputPath) {
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Dataset<Organization> orgs = Utils.readPath(spark, inputPath, Organization.class);
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orgs.createOrReplaceTempView("organization");
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String query = "select country.classname country, legalname.value name, legalshortname.value shortName, websiteurl.value websiteUrl, "
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+
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"collect_set(named_struct(\"pidtype\", pIde.qualifier.classid, \"pid\", pIde.value)) as pidsList, id " +
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"from organization " +
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"lateral view explode( pid) p as pIde " +
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"group by country.classname, legalname.value, legalshortname.value, websiteurl.value, id";
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spark
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.sql(query)
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.as(Encoders.bean(OrganizationInfo.class))
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.write()
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.option("compression", "gzip")
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.mode(SaveMode.Overwrite)
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.json(outputPath);
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}
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}
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